# -*- coding: utf-8 -*-
"""Base class for DeepOBS test problems."""
[docs]class TestProblem(object):
"""Base class for DeepOBS test problems.
Args:
batch_size (int): Batch size to use.
weight_decay (float): Weight decay (L2-regularization) factor to use. If
not specified, the test problems revert to their respective defaults.
Note: Some test problems do not use regularization and this value will
be ignored in such a case.
Attributes:
dataset: The dataset used by the test problem (datasets.DataSet instance).
train_init_op: A tensorflow operation initializing the test problem for the
training phase.
train_eval_init_op: A tensorflow operation initializing the test problem for
evaluating on training data.
test_init_op: A tensorflow operation initializing the test problem for
evaluating on test data.
losses: A tf.Tensor of shape (batch_size, ) containing the per-example loss
values.
regularizer: A scalar tf.Tensor containing a regularization term (might be
a constant 0.0 for test problems that do not use regularization).
accuracy: A scalar tf.Tensor containing the mini-batch mean accuracy.
"""
def __init__(self, batch_size, weight_decay=None):
"""Creates a new test problem instance.
Args:
batch_size (int): Batch size to use.
weight_decay (float): Weight decay (L2-regularization) factor to use. If
not specified, the test problems revert to their respective defaults.
Note: Some test problems do not use regularization and this value will
be ignored in such a case.
"""
self._batch_size = batch_size
self._weight_decay = weight_decay
# Public attributes by which to interact with test problems. These have to
# be created by the set_up function of sub-classes.
self.dataset = None
self.train_init_op = None
self.train_eval_init_op = None
self.test_init_op = None
self.losses = None
self.regularizer = None
self.accuracy = None
[docs] def set_up(self):
"""Sets up the test problem.
This includes setting up the data loading pipeline for the data set and
creating the tensorflow computation graph for this test problem
(e.g. creating the neural network).
"""
raise NotImplementedError(
"""'TestProblem' is an abstract base class, please
use one of the sub-classes.""")